1 to 25 of 94 Semantic Layer Jobs in London

their compliance programs.To learn more about Comply, visit comply.comThe Role:We are looking for Senior AI Data Engineers to implement and operationalize Comply’s semantic layer — turning the ontological models defined by our ontologist and architects into working knowledge graphs, vector search infrastructure, and LLM-powered pipelines. This … hands-on engineering role at the intersection of knowledge representation, AI infrastructure, and data platform engineering. You will own the delivery of semantic layer components, collaborate closely with application and data engineering teams, and ensure that AI-ready data products are reliable, performant, and adopted in practice. ...

picture - product behaviour, GTM performance, commercial data science, financial reporting, and operational intelligence. The Analytics Engineers who serve these teams own the data modelling layer that all of it runs on: dbt models, metric definitions, and semantic layer contributions that analysts, product teams, and AI tools depend … right from the ground up. You'll also engage with the broader Analytics Engineering community across Pleo to drive shared standards, especially around the semantic layer that keeps metrics consistent across the organization.What you'll be doingBuild and maintain dbt models in our new Analytics Warehouse, using ...

cohort LTV, and quantify marketing's contribution to pipeline and bookings, in partnership with our GTM/RevOps analytics.Own marketing data models and the semantic layer. Author dbt models on BigQuery integrating HubSpot, Salesforce, Google Analytics and Amplitude, and own the Omni semantic layer so the team … optimisation and reusable datasets.dbt & a cloud data warehouse (BigQuery, Snowflake or similar) — commercial experience building production models, tests and docs.Modern BI with an integrated semantic layer — building self-serve dashboards and owning metric definitions (e.g. Omni, Looker, Thoughtspot).Deep knowledge of the marketing stack — HubSpot (or similar automation ...

schema fundamental to an FP&A analyst. Responsibilities Define and govern the modelling approach for the client's new data mart: schemaselection, grain, conformeddimensionsand semantic layer structure — with explicit focus on avoiding decisions that foreclose future analytical or AI use cases. Establish data science fundamentals and good practice … meaningful time in an advisory, lead or principal capacity where the deliverable was a recommendation rather than a model. Deepexpertisein dimensional data modelling, schemadesignand semantic layer architecture; able to articulate and defend the trade-offs between competing modelling approaches. Expert SQL; strong Python for analysis and validation. Practical ...

9fin.Explain what's moving the numbers. Diagnose spike drivers and build reproducible analysis frameworks rather than one-off dashboards.Own content datasets and the semantic layer. Author dbt models on BigQuery and own the Omni semantic layer so the newsroom gets fast, trustworthy, self-serve answers.Be the embedded … optimisation and reusable datasets.dbt & a cloud data warehouse (BigQuery, Snowflake or similar) — commercial experience building production models, tests and docs.Modern BI with an integrated semantic layer — building self-serve dashboards and owning metric definitions (e.g. Omni, Looker, Thoughtspot).Engagement and event analytics — designing tracking/instrumentation and analysing ...

similar) and experience integrating with proprietary in-house metadata and event models. Proven design of federated (hub-and-spoke) metadata architectures: a central layer for identity, hierarchy and links, domain-level catalogues with rich local detail, and a clear contract between the two. Practical experience with data governance operating … models: ownership and stewardship roles, sensitivity classification, metadata quality measurement. Semantic layer design: business glossaries and concept registries, resolution of term conflicts between departments, entity resolution, knowledge graph modelling; design-level knowledge of graph databases. Strong consulting and client-facing skills: leading working sessions, defending design decisions ...

means a big push on our BI capabilities, covering new chart types, heatmaps, drilldowns and a reworked dashboard grid, plus targets and budgets, a semantic layer, and AI features including a chat over a customer's own data. What you’ll be doing Performance work. These are dashboards … transaction data, and speed is a feature. Targets and budgets: letting operators set goals per site, per revenue centre, and track against them. Our semantic layer, so metrics mean the same thing everywhere they're used. AI features: dashboard summaries, an AI chat over a customer ...

with business and technical stakeholders to shape solution design, governance, security and best-practice adoption. - Provide technical leadership across FDI deployments, data modelling and semantic layer configuration. - Lead the development and implementation of dashboard and enterprise reporting solutions. - Support the transformation of existing reporting and analytics capabilities into … strong experience in: - Oracle Fusion Data Intelligence (FDI) - Oracle Fusion Cloud Applications - Oracle Analytics Cloud (OAC) - Data analytics and enterprise reporting - Data modelling and semantic layer configuration - Reporting and dashboard solutions - Data integration strategies and architecture - Enterprise reporting and analytics transformations - Security, governance and Oracle Cloud best practices ...

semi-autonomous agent workflows that retrieve, reason over, and act on enterprise data (with guidance on architecture and safety).Semantic Layers & Ontologies - Contribute to semantic models (metrics, definitions, and metadata) that make it easier for business users to query data consistently.LLM-Powered Analytics - Prototype LLM-enabled features for summarisation … explain complex technical concepts to non-technical stakeholders.What Would Make You Stand Out:Experience with LLM orchestration frameworks (e.g., LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel).Exposure to semantic layer technologies (e.g., dbt metrics layer, Cube, AtScale) or knowledge graph tooling.Familiarity with BI platforms (e.g., Qlik, Power ...

semi-autonomous agent workflows that retrieve, reason over, and act on enterprise data (with guidance on architecture and safety).Semantic Layers & Ontologies - Contribute to semantic models (metrics, definitions, and metadata) that make it easier for business users to query data consistently. LLM-Powered Analytics - Prototype LLM-enabled features … explain complex technical concepts to non-technical stakeholders. What Would Make You Stand Out: Experience with LLM orchestration frameworks (e.g., LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel).Exposure to semantic layer technologies (e.g., dbt metrics layer, Cube, AtScale) or knowledge graph tooling. Familiarity with BI platforms (e.g. ...

business requirements into scalable, production-grade data, analytics and AI-enabled solutions.KEY ACCOUNTABILITIESData Product Strategy and Commercial Value• Define target-state data products and semantic layers for key Global Markets domains, including client, trade, market, position, risk and reference data.• Identify use cases where governed data, analytics and automation … governance, lineage, security and production robustness.Data Modelling, Governance and Controls• Work closely with technical and quant teams on domain data modelling, canonical views, silver-layer enterprise views, data catalogues, lineage, metadata and critical data elements.• Provide product-owner challenge to ensure data models are fit for business purpose, support ...

/star schema) for analytics and reporting Provide technical guidance and support to BI Developers during delivery (non-managerial) Contribute to Power BI/semantic layer design to support enterprise reporting Support integration of data from multiple SaaS and third-party systems Ensure best practices across data quality … desirable) Strong background in data warehousing and BI environments Excellent dimensional modelling (Kimball) experience Experience working closely with BI/reporting teams (Power BI, semantic models, DAX) Confident working across end-to-end data pipelines and integration patterns Strong SQL skills with experience optimising queries and datasets Comfortable guiding ...

COPQ) and Demonstrate control environment improvements and reduction in toil to achieve benefits through common tooling and frameworks Uplift Existing Data - Uplift the metadata (semantic layer) of existing data to make it more valuable to users and AI applications (AKA "Brownfield" data enrichment) and Support AI and Natural ...

including identity resolution, consent management, and audience readinessDevelop event streams and triggers to support customer journey orchestration and real-time decisioningProvide structured datasets and semantic layers for dashboards and advanced analyticsImplement data governance practices, including lineage, cataloguing, validation, and GDPR/PII compliancePartner with analytics, MarTech, and marketing teams ...

tailored to the regulatory, sovereignty, and resilience requirements of tier-one financial institutions- Guide customers on building AI-ready data estates: quality, lineage, governance, semantic layers, and retrieval frameworks that enable trustworthy AI grounding at scale- Advise on agentic system architecture — RAG, tool-use patterns, memory and state management ...

portfolio companies.Experience with CDC/replication tools feeding a warehouse from an operational database (MySQL, Postgres)Experience with Looker/LookML or another BI semantic layer.Experience in e-commerce, ticketing, or a marketplace business with high-cardinality partner/catalogue data.Experience building or supporting AI/LLM-facing data ...

Event completeness and coverage Cardinality drift Volume anomalies Identity and user stitching integrity Proactively identify and resolve issues before they impact experiments or reporting Semantic Layer Enablement Enable trusted behavioural metrics through: Databricks metric enabled views Power BI semantic models Ensure metrics are usable for: Self serve … data quality Nice to Have Experience supporting experimentation and A/B testing Knowledge of identity resolution and cross device tracking Power BI semantic modelling experience Experience enabling self serve analytics Interest in AI assisted analytics or metric driven agentsAdditional InformationEmployee discount (hello ASOS discount!) Employee sample sales ...

control. In addition toleadingdata processing thePrincipal Data Engineer will help design and build the DataMeshincluding data modelling andthe processing of datafrom raw through the semantic layers. The Principal Data Engineer willidentifyopportunities for automation and process improvement, coachandmentor data engineers, set coding standards and best practices, implement and document data ...

failures Drive operational efficiency by eliminating the cost of poor data quality through common tooling, frameworks, and proactive control development Enrich the metadata and semantic layer of existing data assets to improve discoverability, usability, and value for AI applications and natural language query capabilities Accelerate adoption of mesh ...

reduce future failuresDrive operational efficiency by eliminating the cost of poor data quality through common tooling, frameworks, and proactive control developmentEnrich the metadata and semantic layer of existing data assets to improve discoverability, usability, and value for AI applications and natural language query capabilitiesAccelerate adoption of mesh data ...

volunteer roles, work experience, etc.)Technical Skill SetData Architecture & Platforms Cloud data platforms, SQL, ingestion pipelines (batch, streaming, CDC), ETL/ELT, data modelling, semantic layers, integration patterns, and the TCO trade-offs of building with hyperscalers vs. Salesforce. Deep familiarity with Informatica (IDMC) for enterprise data integration ...

authorization in one of these countries. Office access available in London, Dublin, and Lisbon.Here's how you'll make a difference:Own the transformation layer in dbt- design, build, and maintain modular, well-tested data models that define how data is structured and consumed across the company.Define and implement … cases.Model complex SaaS data by integrating product events, CRM (Salesforce), and support data into clean, well-defined fact and dimension models.Build and evolve our semantic layer- creating a reliable abstraction over our data that enables consistent KPI definitions and supports downstream consumers, including LLM-based analytics agents.Collaborate with ...

Azure environment. • Hands-on experience working with Databricks, or a strong desire to deepen expertise in it. • Expert understanding of data modelling principles and semantic layer concepts. • Experience working with Azure Data Factory or similar orchestration tools. • Ability to translate business needs into logical, scalable data models. • Comfortable … working across multiple data sources and handling pipeline design. • Experience with Power BI, including semantic models or Tabular Editor. • Curious, collaborative mindset with the ability to push back constructively and guide stakeholders. ...

intervention for standard use cases.Design data ingestion architecture (batch, micro-batch, and streaming) with clear boundaries for system-to-system integration.Define architecture for the semantic layer and self-serve analytics infrastructure.Provide input to data squads for complex data products and support Data Product Managers and Data Engineers where … platform roadmap from an architectural perspective, defining how the platform evolves over time (e.g., SAP BW transition/retirement path, Databricks maturation, Datasphere integration layer decisions).Contribute to enterprise architecture governance forums, representing data platform considerations in broader technology decisions.Provide architectural input to vendor and tooling decisions, evaluating technology ...

standard use cases. Design data ingestion architecture (batch, micro-batch, and streaming) with clear boundaries for system-to-system integration. Define architecture for the semantic layer and self-serve analytics infrastructure. Provide input to data squads for complex data products and support Data Product Managers and Data Engineers … platform roadmap from an architectural perspective, defining how the platform evolves over time (e.g.,SAP BW transition/retirement path, Databricks maturation, Datasphere integration layer decisions). Contribute to enterprise architecture governance forums, representing data platform considerations in broader technology decisions. Provide architectural input to vendor and tooling decisions ...